Zobrazeno 1 - 10
of 14 987
pro vyhledávání: '"MORELLI P"'
This paper introduces a modular, non-deep learning method for filtering and refining sparse correspondences in image matching. Assuming that motion flow within the scene can be approximated by local homography transformations, matches are aggregated
Externí odkaz:
http://arxiv.org/abs/2411.09484
Context. Kinematically decoupled cores (KDCs) are often found in the centers of early-type galaxies. Aims. We aim to investigate the kinematics, structure, and stellar populations of the KDC residing in the early-type galaxy NGC 4494 to understand it
Externí odkaz:
http://arxiv.org/abs/2411.02176
Autor:
Bontà, E. Dalla, Peterson, B. M., Grier, C. J., Berton, M., Brandt, W. N., Ciroi, S., Corsini, E. M., Barba, B. Dalla, Davies, R., Dehghanian, M., Edelson, R., Foschini, L., Gasparri, D., Ho, L. C., Horne, K., Iodice, E., Morelli, L., Pizzella, A., Portaluri, E., Shen, Y., Schneider, D. P., Vestergaard, M.
The goal of this project is to construct an estimator for the masses of supermassive black holes in active galactic nuclei (AGNs) based on the broad Halpha emission line. We make use of published reverberation mapping data. We remeasure all Halpha ti
Externí odkaz:
http://arxiv.org/abs/2410.21387
Autor:
Morelli, Sofia
Accurate multi-decadal wind power predictions are crucial for sustainable energy transitions but are challenged by the coarse spatial resolution of global climate models (GCMs). This study examines the impact of spatial resolution on wind power forec
Externí odkaz:
http://arxiv.org/abs/2410.14681
Autor:
Shukla, Vandita, Morelli, Luca, Trybala, Pawel, Remondino, Fabio, Gan, Wentian, Yu, Yifei, Wang, Xin
UAV-based biodiversity conservation applications have exhibited many data acquisition advantages for researchers. UAV platforms with embedded data processing hardware can support conservation challenges through 3D habitat mapping, surveillance and mo
Externí odkaz:
http://arxiv.org/abs/2409.15914
Autor:
Cacciatore, Alessandro, Morelli, Valerio, Paganica, Federica, Frontoni, Emanuele, Migliorelli, Lucia, Berardini, Daniele
Deep learning has long been dominated by multi-layer perceptrons (MLPs), which have demonstrated superiority over other optimizable models in various domains. Recently, a new alternative to MLPs has emerged - Kolmogorov-Arnold Networks (KAN)- which a
Externí odkaz:
http://arxiv.org/abs/2409.13550
A critical step in the digital surface models(DSM) generation is feature matching. Off-track (or multi-date) satellite stereo images, in particular, can challenge the performance of feature matching due to spectral distortions between images, long ba
Externí odkaz:
http://arxiv.org/abs/2409.02825
Notch signaling is a ubiquitous and versatile intercellular signaling system that drives collective behaviors and pattern formation in biological tissues. During embryonic development, Notch is involved in generation of collective biochemical oscilla
Externí odkaz:
http://arxiv.org/abs/2408.04027
Autor:
Zhan, Zongqian, Yu, Yifei, Xia, Rui, Gan, Wentian, Xie, Hong, Perda, Giulio, Morelli, Luca, Remondino, Fabio, Wang, Xin
In the last twenty years, Structure from Motion (SfM) has been a constant research hotspot in the fields of photogrammetry, computer vision, robotics etc., whereas real-time performance is just a recent topic of growing interest. This work builds upo
Externí odkaz:
http://arxiv.org/abs/2407.03939
Autor:
Angthopo, J., Granett, B. R., La Barbera, F., Longhetti, M., Iovino, A., Fossati, M., Ditrani, F. R., Costantin, L., Zibetti, S., Gallazzi, A., Sánchez-Blázquez, P., Tortora, C., Spiniello, C., Poggianti, B., Vazdekis, A., Balcells, M., Bardelli, S., Benn, C. R., Bianconi, M., Bolzonella, M., Busarello, G., Cassarà, L. P., Corsini, E. M., Cucciati, O., Dalton, G., Ferré-Mateu, A., García-Benito, R., Delgado, R. M. González, Gafton, E., Gullieuszik, M., Haines, C. P., Iodice, E., Ikhsanova, A., Jin, S., Knapen, J. H., McGee, S., Mercurio, A., Merluzzi, P., Morelli, L., Moretti, A., Murphy, D. N. A., Pizzella, A., Pozzetti, L., Ragusa, R., Trager, S. C., Vergani, D., Vulcani, B., Talia, M., Zucca, E.
The WHT Enhanced Area Velocity Explorer (WEAVE) is a new, massively multiplexing spectrograph. This new instrument will be exploited to obtain high S/N spectra of $\sim$25000 galaxies at intermediate redshifts for the WEAVE Stellar Population Survey
Externí odkaz:
http://arxiv.org/abs/2406.11748